A novel immune classification reveals distinct immune escape mechanism and genomic alterations: implications for immunotherapy in hepatocellular carcinoma

High ratio of resident to exhausted CD4 + T cells predicts favorable prognosis and potentially better immunotherapeutic efficacy in hepatocellular carcinoma

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) are significantly implicated in regulating the tumor immune microenvironment (TIME) and immunotherapeutic response. However, little is known about the impact of the resident and exhausted status of TILs in hepatocellular carcinoma (HCC).

METHODS

Single-cell RNA sequencing data was applied to discover resident and exhausted signatures of TILs. Survival outcomes, biological function, immune infiltration, genomic variation, immunotherapeutic efficacy, and sorafenib response were further explored the clinical significance and molecular association of TILs in HCC. Moreover, a candidate gene with predictive capability for the dismal subtype was identified through univariate Cox regression analysis, survival analysis, and the BEST website.

RESULTS

Single-cell analysis revealed that CD8 + T, CD4 + T, and NK cells were strongly associated with resident and exhausted patterns. Specific resident and exhausted signatures for each subpopulation were extracted in HCC. Further multivariate Cox analysis revealed that the ratio of resident to exhausted CD4 + T cells in TIME was an independent prognostic factor. After incorporating tumor purity with the ratio of resident to exhausted CD4 + T cells, we stratified HCC patients into three subtypes and found that (i) CD4 residencyhighexhaustionlow subtype was endowed with favorable prognosis, immune activation, and sensitivity to immunotherapy; (ii) CD4 exhaustionhighresidencylow subtype was characterized by genome instability and sensitivity to sorafenib; (iii) Immune-desert subtype was associated with malignant-related pathways and poor prognosis. Furthermore, spindle assembly abnormal protein 6 homolog (SASS6) was identified as a key gene, which accurately predicted the immune-desert subtype. Prognostic analysis as well as in vitro and in vivo experiments further demonstrated that SASS6 was closely associated with tumor prognosis, proliferation, and migration.

CONCLUSIONS

The ratio of resident to exhausted CD4 + T cells shows promise as a potential biomarker for HCC prognosis and immunotherapy response and SASS6 may serve as a biomarker and therapeutic target for prognostic assessment of HCC.

Luteolin exerts anti-tumour immunity in hepatocellular carcinoma by accelerating CD8+ T lymphocyte infiltration

Luteolin, a commonly used traditional Chinese medicine, has been utilized for several decades in the treatment of hepatocellular carcinoma (HCC). Previous research has demonstrated its anti-tumour efficacy, but its underlying mechanism remains unclear. This study aimed to assess the therapeutic effects of luteolin in H22 tumour-bearing mice. luteolin effectively inhibited the growth of solid tumours in a well-established mouse model of HCC. High-throughput sequencing revealed that luteolin treatment could enhance T-cell activation, cell chemotaxis and cytokine production. In addition, luteolin helped sustain a high ratio of CD8+ T lymphocytes in the spleen, peripheral blood and tumour tissues. The effects of luteolin on the phenotypic and functional changes in tumour-infiltrating CD8+ T lymphocytes were also investigated. Luteolin restored the cytotoxicity of tumour-infiltrating CD8+ T lymphocytes in H22 tumour-bearing mice. The CD8+ T lymphocytes exhibited intensified phenotype activation and increased production of granzyme B, IFN-γ and TNF-α in serum. The combined administration of luteolin and the PD-1 inhibitor enhanced the anti-tumour effects in H22 tumour-bearing mice. Luteolin could exert an anti-tumour immune response by inducing CD8+ T lymphocyte infiltration and enhance the anti-tumour effects of the PD-1 inhibitor on H22 tumour-bearing mice.

The association between tumour heterogeneity and immune evasion mechanisms in hepatocellular carcinoma and its clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. The emergence of combination therapy, atezolizumab (anti-PDL1, immune checkpoint inhibitor) and bevacizumab (anti-VEGF) has revolutionised the management of HCC. Despite this breakthrough, the best overall response rate with first-line systemic therapy is only about 30%, owing to intra-tumoural heterogeneity, complex tumour microenvironment and the lack of predictive biomarkers. Many groups have attempted to classify HCC based on the immune microenvironment and have consistently observed better outcomes in immunologically "hot" HCC. We summarised possible mechanisms of tumour immune evasion based on the latest literature and the rationale for combination/sequential therapy to improve treatment response. Lastly, we proposed future strategies and therapies to overcome HCC immune evasion to further improve treatment outcomes of HCC.

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

PHLDA2 reshapes the immune microenvironment and induces drug resistance in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignancy known for its unfavorable prognosis. The dysregulation of the tumor microenvironment (TME) can affect the sensitivity to immunotherapy or chemotherapy, leading to treatment failure. The elucidation of PHLDA2's involvement in HCC is imperative, and the clinical value of PHLDA2 is also underestimated. Here, bioinformatics analysis was performed in multiple cohorts to explore the phenotype and mechanism through which PHLDA2 may affect the progression of HCC. Then, the expression and function of PHLDA2 were examined via the qRT-PCR, Western Blot, and MTT assays. Our findings indicate a substantial upregulation of PHLDA2 in HCC, correlated with a poorer prognosis. The methylation levels of PHLDA2 were found to be lower in HCC tissues compared to normal liver tissues. Besides, noteworthy associations were observed between PHLDA2 expression and immune infiltration in HCC. In addition, PHLDA2 upregulation is closely associated with stemness features and immunotherapy or chemotherapy resistance in HCC. In vitro experiments showed that sorafenib or cisplatin significantly up-regulated PHLDA2 mRNA levels, and PHLDA2 knockdown markedly decreased the sensitivity of HCC cells to chemotherapy drugs. Meanwhile, we found that TGF-β induced the expression of PHLDA2 in vitro. The GSEA and in vitro experiment indicated that PHLDA2 may promote the HCC progression via activating the AKT signaling pathway. Our study revealed the novel role of PHLDA2 as an independent prognostic factor, which plays an essential role in TME remodeling and treatment resistance in HCC.

Treatment Options for Hepatocellular Carcinoma Using Immunotherapy: Present and Future

Hepatocellular carcinoma (HCC) is a common cancer, and the body's immune responses greatly affect its progression and the prognosis of patients. Immunological suppression and the maintenance of self-tolerance in the tumor microenvironment are essential responses, and these form part of the theoretical foundations of immunotherapy. In this review, we first discuss the tumor microenvironment of HCC, describe immunosuppression in HCC, and review the major biomarkers used to track HCC progression and response to treatment. We then examine antibody-based therapies, with a focus on immune checkpoint inhibitors (ICIs), monoclonal antibodies that target key proteins in the immune response (programmed cell death protein 1, anti-cytotoxic T-lymphocyte associated protein 4, and programmed death-ligand 1) which have transformed the treatment of HCC and other cancers. ICIs may be used alone or in conjunction with various targeted therapies for patients with advanced HCC who are receiving first-line treatments or subsequent treatments. We also discuss the use of different cellular immunotherapies, including T cell receptor (TCR) T cell therapy and chimeric antigen receptor (CAR) T cell therapy. We then review the use of HCC vaccines, adjuvant immunotherapy, and oncolytic virotherapy, and describe the goals of future research in the development of treatments for HCC.

Neuronal cell cycle reentry events in the aging brain are more prevalent in neurodegeneration and lead to cellular senescence

Increasing evidence indicates that terminally differentiated neurons in the brain may recommit to a cell cycle-like process during neuronal aging and under disease conditions. Because of the rare existence and random localization of these cells in the brain, their molecular profiles and disease-specific heterogeneities remain unclear. Through a bioinformatics approach that allows integrated analyses of multiple single-nucleus transcriptome datasets from human brain samples, these rare cell populations were identified and selected for further characterization. Our analyses indicated that these cell cycle-related events occur predominantly in excitatory neurons and that cellular senescence is likely their immediate terminal fate. Quantitatively, the number of cell cycle re-engaging and senescent neurons decreased during the normal brain aging process, but in the context of late-onset Alzheimer's disease (AD), these cells accumulate instead. Transcriptomic profiling of these cells suggested that disease-specific differences were predominantly tied to the early stage of the senescence process, revealing that these cells presented more proinflammatory, metabolically deregulated, and pathology-associated signatures in disease-affected brains. Similarly, these general features of cell cycle re-engaging neurons were also observed in a subpopulation of dopaminergic neurons identified in the Parkinson's disease (PD)-Lewy body dementia (LBD) model. An extended analysis conducted in a mouse model of brain aging further validated the ability of this bioinformatics approach to determine the robust relationship between the cell cycle and senescence processes in neurons in this cross-species setting.

Identification and prognostic analysis of ferroptosis‑related gene HSPA5 to predict the progression of lung squamous cell carcinoma

Ferroptosis, an iron-dependent form of regulated cell death driven by excessive lipid peroxidation, is implicated in the development and therapeutic responses of cancer. However, the role of ferroptosis-related gene profiles in lung squamous cell carcinoma (LSCC) remains largely unknown. The present study aimed to identify the prognostic roles of ferroptosis-related genes in LSCC. Sequencing data from the Cancer Genome Atlas were analyzed and ferroptosis-related gene expression between tumor and para-tumor tissue was identified. The prognostic role of these genes was also assessed using Kaplan-Meier analyses and univariate and multivariate Cox proportional hazards regression model analyses. Immunological correlation, tumor stemness, drug sensitivity and the transcriptional differences of heat shock protein (HSP)A5 in LSCC were also analyzed. Thereafter, the expression of HSPA5 in 100 patients with metastatic LSCC was evaluated using immunohistochemistry (IHC) and the clinical significance of these markers with different risk factors was assessed. Of the 22 ferroptosis-related genes, the expression of HSPA5, HSPB1, glutathione peroxidase 4, Fanconi anemia complementation group D2, CDGSH iron sulfur domain 1, farnesyl-diphosphate farnesyltransferase 1, nuclear factor erythroid 2 like 2, solute carrier (SLC)1A5, ribosomal protein L8, nuclear receptor coactivator 4, transferrin receptor and SLC7A11 was significantly increased in LSCC compared with adjacent tissues. However, only high expression of HSPA5 was able to predict progression-free survival (PFS) and disease-free survival in LSCC. Although HSPA5 was also significantly elevated in patients with lung adenocarcinoma, HSPA5 expression did not predict the prognosis of patients with lung adenocarcinoma. Of note, a higher expression of HSPA5 was related to higher responses to chemotherapy but not to immunotherapy. In addition, HSPA5 expression was positively correlated with 'ferroptosis', 'cellular responses to hypoxia', 'tumor proliferation signature', 'G2M checkpoint', 'MYC targets' and 'TGFB'. IHC analysis also demonstrated that a high expression of HSPA5 in patients with metastatic LSCC in the study cohort was associated with shorter PFS and overall survival. In conclusion, the present study demonstrated that the expression of the ferroptosis-related gene HSPA5 may be a negative prognostic marker for LSCC.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

Aberrant R-loop-mediated immune evasion, cellular communication, and metabolic reprogramming affect cancer progression: a single-cell analysis

Dysregulation of R-loop homeostasis is closely related to various human diseases, including cancer. However, the causality of aberrant R-loops in tumor progression remains unclear. In this study, using single-cell RNA-sequencing datasets from lung adenocarcinoma (LUAD), we constructed an R-loop scoring model to characterize the R-loop state according to the identified R-loop regulators related to EGFR mutations, tissue origins, and TNM stage. We then evaluated the relationships of the R-loop score with the tumor microenvironment (TME) and treatment response. Furthermore, the potential roles of FANCI-mediated R-loops in LUAD were explored using a series of in vitro experiments. Results showed that malignant cells with low R-loop scores displayed glycolysis and epithelial-mesenchymal transition pathway activation and immune escape promotion, thereby hampering the antitumor therapeutic effects. Cell communication analysis suggested that low R-loop scores contributed to T cell exhaustion. We subsequently validated the prognostic value of R-loop scores by using bulk transcriptome datasets across 33 tumor types. The R-loop scoring model well predicted patients' therapeutic response to targeted therapy, chemotherapy, or immunotherapy in 32 independent cohorts. Remarkably, changes in R-loop distribution mediated by FANCI deficiency blocked the activity of Ras signaling pathway, suppressing tumor-cell proliferation and dissemination. In conclusion, this study reveals the underlying molecular mechanism of metabolic reprogramming and T cell exhaustion under R-loop score patterns, and the changes in R-loops mediated by R-loop regulators resulting in tumor progression. Therefore, incorporating anticancer methods based on R-loop or R-loop regulators into the treatment schemes of precision medicine may be beneficial.

A pan-cancer analysis revealing the role of LFNG, MFNG and RFNG in tumor prognosis and microenvironment

BACKGROUND

Fringe is a glycosyltransferase involved in tumor occurrence and metastasis. However, a comprehensive analysis of the Fringe family members lunatic fringe (LFNG), manic fringe (MFNG), radical fringe (RFNG) in human cancers is lacking.

METHODS

In this study, we performed a pan-cancer analysis of Fringe family members in 33 cancer types with transcriptomic, genomic, methylation data from The Cancer Genome Atlas (TCGA) project. The correlation between Fringe family member expression and patient overall survival, copy number variation, methylation, Gene Ontology enrichment, and tumor-infiltrating lymphocytes (TILs) was investigated by using multiple databases, such as cBioPortal, Human Protein Atlas, GeneCards, STRING, MSigDB, TISIDB, and TIMER2. In vitro experiments and immunohistochemical assays were performed to validate our findings.

RESULTS

High expression levels of LFNG, MFNG, RFNG were closely associated with poor overall survival in multiple cancers, particularly in pancreatic adenocarcinoma (PAAD), uveal melanoma (UVM), and brain lower-grade glioma (LGG). Copy number variation analysis revealed that diploid and gain mutations of LFNG was significantly increased in PAAD and stomach adenocarcinoma (STAD), and significantly associated with the methylation levels in promoter regions. Significant differential genes between high and low expression groups of these Fringe family members were found to be consistently enriched in immune response and T cell activation pathway, extracellular matrix adhesion pathway, RNA splicing and ion transport pathways. Correlation between the abundance of tumor-infiltrating lymphocytes (TILs) and LFNG, MFNG, and RFNG expression showed that high LFNG expression was associated with lower TIL levels, particularly in PAAD. In vitro experiment by using pancreatic cancer PANC1 cells showed that LFNG overexpression promoted cell proliferation and invasion. Immunohistochemical assay in 90 PAAD patients verified the expression level of LFNG and its relationship with the prognosis.

CONCLUSIONS

Our study provides a relatively comprehensive understanding of the expression, mutation, copy number, promoter methylation level changes along with prognosis values of LFNG, MFNG, and RFNG in different tumors. High LFNG expression may serve as a poor prognosis molecular marker for PAAD.

Inflammatory response-based prognostication and personalized therapy decisions in clear cell renal cell cancer to aid precision oncology

OBJECTIVE

The impact of inflammatory response on tumor development and therapeutic response is of significant importance in clear cell renal cell carcinoma (ccRCC). The customization of specialized prognostication approaches and the exploration of supplementary treatment options hold critical clinical implications in relation to the inflammatory response.

METHODS

In the present study, unsupervised clustering was implemented on TCGA-KIRC tumors using transcriptome profiles of inflammatory response genes, which was then validated in two ccRCC datasets (E-MATB-1980 and ICGC) and two immunotherapy datasets (IMvigor210 and Liu et al.) via SubMap and NTP algorithms. Combining co-expression and LASSO analyses, inflammatory response-based scoring system was defined, which was evaluated in pan-cancer.

RESULTS

Three reproducible inflammatory response subtypes (named IR1, IR2 and IR3) were determined and independently verified, each exhibiting distinct molecular, clinical, and immunological characteristics. Among these subtypes, IR2 had the best OS outcomes, followed by IR3 and IR1. In terms of anti-angiogenic agents, sunitinib may be appropriate for IR1 patients, while axitinib and pazopanib may be suitable for IR2 patients, and sorafenib for IR3 patients. Additionally, IR1 patients might benefit from anti-CTLA4 therapy. A scoring system called IRscore was defined for individual ccRCC patients. Patients with high IRscore presented a lower response rate to anti-PD-L1 therapy and worse prognostic outcomes. Pan-cancer analysis demonstrated the immunological features and prognostic relevance of the IRscore.

CONCLUSION

Altogether, characterization of inflammatory response subtypes and IRscore provides a roadmap for patient risk stratification and personalized treatment decisions, not only in ccRCC, but also in pan-cancer.

Genome-scale CRISPR-Cas9 screening stratifies pancreatic cancer with distinct outcomes and immunotherapeutic efficacy

Pancreatic cancer (PC) was featured by dramatic heterogeneity and dismal outcomes. An ideal classification strategy capable of achieving risk stratification and individualized treatment is urgently needed to significantly improve prognosis. In this study, using the 105 prognostic cancer essential genes identified by genome-scale CRISPR-Cas9 screening and univariate Cox analysis, we established and verified three heterogeneous subtypes via non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms in the TCGA-PAAD cohort (176 samples) and four multi-center cohorts (233 samples), respectively. Among them, C1 with the worst prognosis was enriched in immune-related pathways, possessed superior infiltration abundance of immune cells and immune checkpoint molecules expression, and might be most sensitive to immunotherapy. C3, owing a moderate prognosis, might be featured by proliferative biological function, and despite its highest immunogenicity, the defects in antigen processing and presentation ability coupled with barren immune environment render it ineffective for immunotherapy, while it had potential sensitivity to paclitaxel and methotrexate. Besides, C2 harbored the best prognosis and was characterized by metabolism-related functions. These results could deepen our understanding of PC molecular heterogeneity and provide a trustworthy reference for prognostic stratification management and precision medicine in clinical practice.

From Reductionistic Approach to Systems Immunology Approach for the Understanding of Tumor Microenvironment

The tumor microenvironment (TME) is a complex and dynamic ecosystem that includes a variety of immune cells mutually interacting with tumor cells, structural/stromal cells, and each other. The immune cells in the TME can have dual functions as pro-tumorigenic and anti-tumorigenic. To understand such paradoxical functions, the reductionistic approach classifies the immune cells into pro- and anti-tumor cells and suggests the therapeutic blockade of the pro-tumor and induction of the anti-tumor immune cells. This strategy has proven to be partially effective in prolonging patients' survival only in a fraction of patients without offering a cancer cure. Recent advances in multi-omics allow taking systems immunology approach. This essay discusses how a systems immunology approach could revolutionize our understanding of the TME by suggesting that internetwork interactions of the immune cell types create distinct collective functions independent of the function of each cellular constituent. Such collective function can be understood by the discovery of the immunological patterns in the TME and may be modulated as a therapeutic means for immunotherapy of cancer.

Multi-omics analysis uncovers clinical, immunological, and pharmacogenomic implications of cuproptosis in clear cell renal cell carcinoma

OBJECTIVE

The latest research proposed a novel copper-dependent programmed cell death named cuproptosis. We aimed to elucidate the influence of cuproptosis in clear cell renal cell carcinoma (ccRCC) from a multi-omic perspective.

METHODS

This study systematically assessed mRNA expression, methylation, and genetic alterations of cuproptosis genes in TCGA ccRCC samples. Through unsupervised clustering analysis, the samples were classified as different cuproptosis subtypes, which were verified through NTP method in the E-MTAB-1980 dataset. Next, the cuproptosis score (Cuscore) was computed based on cuproptosis-related genes via PCA. We also evaluated clinical and immunogenomic features, drug sensitivity, immunotherapeutic response, and post-transcriptional regulation.

RESULTS

Cuproptosis genes presented multi-layer alterations in ccRCC, and were linked with patients' survival and immune microenvironment. We defined three cuproptosis subtypes [C1 (moderate cuproptosis), C2 (low cuproptosis), and C3 (high cuproptosis)], and the robustness and reproducibility of this classification was further proven. Overall survival was best in C3, moderate in C1, and worst in C2. C1 had the highest sensitivity to pazopanib, and sorafenib, while C2 was most sensitive to sunitinib. Furthermore, C1 patients benefited more from anti-PD-1 immunotherapy. Patients with high Cuscore presented the notable survival advantage. Cuscore was highly linked with immunogenomic features, and post-transcriptional events that contributed to ccRCC development. Finally, several potential compounds and druggable targets (NMU, RARRES1) were selected for low Cuscore group.

CONCLUSION

Overall, our study revealed the non-negligible role of cuproptosis in ccRCC development. Evaluation of the cuproptosis subtypes improves our cognition of immunogenomic features and better guides personalized prognostication and precision therapy.

Potential role of gut microbes in the efficacy and toxicity of immune checkpoints inhibitors

In recent years, Immune checkpoint inhibitors have been extensively used in the treatment of a variety of cancers. However, the response rates ranging from 13% to 69% depending on the tumor type and the emergence of immune-related adverse events have posed significant challenges for clinical treatment. As a key environmental factor, gut microbes have a variety of important physiological functions such as regulating intestinal nutrient metabolism, promoting intestinal mucosal renewal, and maintaining intestinal mucosal immune activity. A growing number of studies have revealed that gut microbes further influence the anticancer effects of tumor patients through modulation of the efficacy and toxicity of immune checkpoint inhibitors. Currently, faecal microbiota transplantation (FMT) have been developed relatively mature and suggested as an important regulator in order to enhance the efficacy of treatment. This review is dedicated to exploring the impact of differences in flora composition on the efficacy and toxicity of immune checkpoint inhibitors as well as to summarizing the current progress of FMT.

Systematic analysis of transcriptome signature for improving outcomes in lung adenocarcinoma

PURPOSE

The updated guidelines highlight gene expression-based multigene panel as a critical tool to assess overall survival (OS) and improve treatment for lung adenocarcinoma (LUAD) patients. Nevertheless, genome-wide expression signatures are still limited in real clinical utility because of insufficient data utilization, a lack of critical validation, and inapposite machine learning algorithms.

METHODS

2330 primary LUAD samples were enrolled from 11 independent cohorts. Seventy-six algorithm combinations based on ten machine learning algorithms were applied. A total of 108 published gene expression signatures were collected. Multiple pharmacogenomics databases and resources were utilized to identify precision therapeutic drugs.

RESULTS

We comprehensively developed a robust machine learning-derived genome-wide expression signature (RGS) according to stably OS-associated RNAs (OSRs). RGS was an independent risk element and remained robust and reproducible power by comparing it with general clinical parameters, molecular characteristics, and 108 published signatures. RGS-based stratification possessed different biological behaviors, molecular mechanisms, and immune microenvironment patterns. Integrating multiple databases and previous studies, we identified that alisertib was sensitive to the high-risk group, and RITA was sensitive to the low-risk group.

CONCLUSION

Our study offers an appealing platform to screen dismal prognosis LUAD patients to improve clinical outcomes by optimizing precision therapy.

A novel cuproptosis-related gene model predicts outcomes and treatment responses in pancreatic adenocarcinoma

BACKGROUND

Cuproptosis is recently emerging as a hot spot in cancer research. However, its role in pancreatic adenocarcinoma (PAAD) has not yet been clarified. This study aimed to explore the prognostic and therapeutic implications of cuproptosis-related genes in PAAD.

METHODS

Two hundred thirteen PAAD samples from the International Cancer Genome Consortium (ICGC) were split into training and validation sets in the ratio of 7:3. The Cox regression analyses generated a prognostic model using the ICGC cohort for training (n = 152) and validation (n = 61). The model was externally tested on the Gene Expression Omnibus (GEO) (n = 80) and The Cancer Genome Atlas (TCGA) datasets (n = 176). The clinical characteristics, molecular mechanisms, immune landscape, and treatment responses in model-defined subgroups were explored. The expression of an independent prognostic gene TSC22D2 was confirmed by public databases, real-time quantitative PCR (RT-qPCR), western blot (WB), and immunohistochemistry (IHC).

RESULTS

A prognostic model was established based on three cuproptosis-related genes (TSC22D2, C6orf136, PRKDC). Patients were stratified into high- and low-risk groups using the risk score based on this model. PAAD patients in the high-risk group had a worse prognosis. The risk score was statistically significantly correlated with most clinicopathological characteristics. The risk score based on this model was an independent predictor of overall survival (OS) (HR = 10.7, p < 0.001), and was utilized to create a scoring nomogram with excellent prognostic value. High-risk patients had a higher TP53 mutation rate and a superior response to multiple targeted therapies and chemotherapeutic drugs, but might obtain fewer benefits from immunotherapy. Moreover, elevated TSC22D2 expression was discovered to be an independent prognostic predictor for OS (p < 0.001). Data from public databases and our own experiments showed that TSC22D2 expression was significantly higher in pancreatic cancer tissues/cells compared to normal tissues/cells.

CONCLUSION

This novel model based on cuproptosis-related genes provided a robust biomarker for predicting the prognosis and treatment responses of PAAD. The potential roles and underlying mechanisms of TSC22D2 in PAAD need further explored.

M6A regulator-mediated immune infiltration and methylation modification in hepatocellular carcinoma microenvironment and immunotherapy

Introduction: Tremendous evidence indicates that N6-methyladenosine (m6A) epigenetic modification and m6A-related enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of the m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive. Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value was compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Four independent algorithms (ssGSEA, xCell, MCP-counter, and TIMER) were used to calculate the ratio of tumor cells and non-tumor cells to evaluate the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs was performed using TIDE and SubMap. Results: A total of 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. The m6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways, and immune cell infiltration abundance under distinct m6A patterns. As expected, the m6A gene cluster confirmed the aforementioned results. The m6Ascore model further found that patients in the high-m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, upregulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low-m6Ascore patients were associated with adverse outcomes. Notably, low-m6Ascore patients might be more sensitive to anti-PD-L1 therapy. Conclusion: This study found that a classification model based on the m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision-making.

Identification and validation of a potential key gene SGOL1 for poor prognosis in hepatocellular carcinoma based on a bioinformatics approach

OBJECTIVE

Hepatocellular carcinoma (HCC) is one of the most prevalent types of cancer worldwide. Shugoshin 1 (SGOL1) plays a crucial role in cell mitosis and its aberrant expression level in human tumors has shown to promote chromosomal instability (CIN) and accelerate tumor growth. SGOL1 expression level in HCC cells and tissues, whether it has an influence on HCC patients' prognosis, and its mechanism of action have not yet been studied.

METHODS

We carried out the bioinformatics analysis of SGOL1 expression level and survival analysis in 8 different malignancies, including HCC. In addition, we analyzed SGOL1 expression level in HCC tissues, as well as HCC patients' clinical features, enrichment analysis of SGOL1 function and mechanism of action in HCC and tumor immune cells. The effects of SGOL1 expression level and cell viability on HCC were confirmed by in vitro cytological assays.

RESULTS

It was found that SGOL1 mRNA expression level was significantly higher in several tumor tissues, including HCC, than in corresponding normal tissues, and the elevated SGOL1 expression level was strongly associated with HCC patients' poor prognosis. It was also revealed that SGOL1 expression level in HCC tissue was positively correlated with disease stage, tumor grade, and tumor size, and the results of multivariate logistic regression analysis showed that SGOL1 was one of the independent influential factors of the prognosis of HCC. Enrichment analysis revealed that SGOL1 expression level in HCC tissue was mainly associated with tumor proliferation, cell cycle, and other factors. The results of the immune infiltration analysis indicated that SGOL1 expression level was associated with immune cell infiltration and immune checkpoints in HCC. In vitro experiments demonstrated the high SGOL1 expression level in HCC tissues and cells, and silencing of SGOL1 resulted in altered cell cycle markers and decreased proliferation, invasion, and migration of HCC cells.

CONCLUSION

The findings revealed that SGOL1 is highly expressed in HCC tissues, it is a biomarker of a poor prognosis, which may be related to immune cell infiltration in HCC, and may enhance the proliferation, invasion, and migration of HCC cells. The results may provide new insights into targeted treatment of HCC and improve HCC patients' prognosis.

Gene interaction perturbation network deciphers a high-resolution taxonomy in colorectal cancer

Molecular subtypes of colorectal cancer (CRC) are currently identified via the snapshot transcriptional profiles, largely ignoring the dynamic changes of gene expressions. Conversely, biological networks remain relatively stable irrespective of time and condition. Here, we introduce an individual-specific gene interaction perturbation network-based (GIN) approach and identify six GIN subtypes (GINS1-6) with distinguishing features: (i) GINS1 (proliferative, 24%~34%), elevated proliferative activity, high tumor purity, immune-desert, PIK3CA mutations, and immunotherapeutic resistance; (ii) GINS2 (stromal-rich, 14%~22%), abundant fibroblasts, immune-suppressed, stem-cell-like, SMAD4 mutations, unfavorable prognosis, high potential of recurrence and metastasis, immunotherapeutic resistance, and sensitive to fluorouracil-based chemotherapy; (iii) GINS3 (KRAS-inactivated, 13%~20%), high tumor purity, immune-desert, activation of EGFR and ephrin receptors, chromosomal instability (CIN), fewer KRAS mutations, SMOC1 methylation, immunotherapeutic resistance, and sensitive to cetuximab and bevacizumab; (iv) GINS4 (mixed, 10%~19%), moderate level of stromal and immune activities, transit-amplifying-like, and TMEM106A methylation; (v) GINS5 (immune-activated, 12%~24%), stronger immune activation, plentiful tumor mutation and neoantigen burden, microsatellite instability and high CpG island methylator phenotype, BRAF mutations, favorable prognosis, and sensitive to immunotherapy and PARP inhibitors; (vi) GINS6, (metabolic, 5%~8%), accumulated fatty acids, enterocyte-like, and BMP activity. Overall, the novel high-resolution taxonomy derived from an interactome perspective could facilitate more effective management of CRC patients.

Clinical value of identifying genes that inhibit hepatocellular carcinomas

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the fourth most frequent cause of cancer-related death in the world. The most common histological type of liver cancer is hepatocellular carcinoma (HCC, 75-80%).

AREAS COVERED

Based on primary literature, this review provides an updated analysis of studies of genetic characterization of HCC at the level of gene mutation profiling, copy number alterations and gene expression, with definition of molecular subgroups and identification of some molecular biomarkers and therapeutic targets.

EXPERT OPINION

A detailed and comprehensive study of the genetic abnormalities characterizing different HCC subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of these tumors may provide a fundamental contribution to improve the survival of a subset of HCC patients. Immunotherapy represents a new fundamental strategy for the treatment of HCC.

Tertiary lymphoid structures: Associated multiple immune cells and analysis their formation in hepatocellular carcinoma

The prognostic value of immune cells in tertiary lymphoid structures (TLSs) remains unclear in hepatocellular carcinoma (HCC). Here, 59 of 145 patients had TLSs in training set, 48 of 120 patients had TLSs in testing set. Immunohistochemistry (IHC) were used to label CD3+ T cells, CD20+ B cells, CD8+ T cells, CD208+ dendritic cells, and CD21+ follicular dendritic cells in TLSs. High CD20+, CD208+, and CD8+ cell densities were favorable prognostic factors for overall survival (OS). High CD3+, CD20+, CD208+, and CD8+ cell densities were significantly associated with reduced early recurrence. TLSs were divided into three grades (A, B, and C) based on immune cell density. Patients with grade C or B had significantly improved OS. Patients with grade C had the lowest recurrence rate, followed by those with grade B, while patients with grade A had the highest recurrence rate. The stromal, immune, and ESTIMATE scores derived from the ESTIMATE package were significantly higher and tumor purity was significantly lower in patients with TLSs. Patients with TLSs had significantly higher relative numbers of memory B cells, plasma cells, CD8+ T cells, NK cells, and dendritic cells and lower relative numbers of Treg cells, macrophages, and M2 macrophages according to the CIBERSORT assessment. Bioinformatics analysis and experiments confirmed that KLRK1 and GZMA expression are associated TLSs formation and can predict TLSs existence. Grade B and grade C were favorable prognostic factors for OS and recurrence and could represent immune-active tumors.

The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance

The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.

Definition of a Novel Cuproptosis-Relevant lncRNA Signature for Uncovering Distinct Survival, Genomic Alterations, and Treatment Implications in Lung Adenocarcinoma

Objective

Cuproptosis is a newly discovered copper-independent cell death modality, and limited evidence suggests the critical implications in human cancers. Nonetheless, the clinical impacts of cuproptosis-relevant lncRNAs in lung adenocarcinoma (LUAD) remain largely ill-defined. The present study was aimed at defining a cuproptosis-relevant lncRNA signature for LUAD and discuss the clinical utility.

Methods

We collected transcriptome expression profiling, clinical information, somatic mutation, and copy number variations from TCGA-LUAD cohort retrospectively. The genetic alterations of cuproptosis genes were systematically assessed across LUAD, and cuproptosis-relevant lncRNAs were screened for defining a LASSO prognostic model. Genomic alterations, immunological and stemness features, and therapeutic sensitivity were studied with a series of computational approaches.

Results

Cuproptosis genes displayed aberrant expression and widespread genomic alterations across LUAD, potentially modulated by m6A/m5C/m1A RNA modification mechanisms. We defined a cuproptosis-relevant lncRNA signature, with a reliable efficacy in predicting clinical outcomes. High-risk subset displayed higher somatic mutations, CNVs, TMB, SNV neoantigens, aneuploidy score, CTA score, homologous recombination defects, and intratumor heterogeneity, cytolytic activity, CD8+ T effector, and antigen processing machinery, proving that this subset might benefit from immunotherapy. Increased stemness indexes and activity of oncogenic pathways might contribute to undesirable prognostic outcomes for high-risk subset. Additionally, high-risk patients generally exhibited higher response to chemotherapeutic agents (cisplatin, etc.). We also predicted several small molecule compounds (GSK461364, KX2-391, etc.) for treating this subset.

Conclusion

Accordingly, this cuproptosis-relevant lncRNA signature offers an efficient approach to identify and characterize diverse prognosis, genomic alterations, and treatment outcomes in LUAD, thus potentially assisting personalized therapy.

Integrated profiling of endoplasmic reticulum stress-related DERL3 in the prognostic and immune features of lung adenocarcinoma

Background

DERL3 has been implicated as an essential element in the degradation of misfolded lumenal glycoproteins induced by endoplasmic reticulum (ER) stress. However, the correlation of DERL3 expression with the malignant phenotype of lung adenocarcinoma (LUAD) cells is unclear and remains to be elucidated. Herein, we investigated the interaction between the DERL3 and LUAD pathological process.

Methods

The Cancer Genome Atlas (TCGA) database was utilized to determine the genetic alteration of DERL3 in stage I LUAD. Clinical LUAD samples including carcinoma and adjacent tissues were obtained and were further extracted to detect DERL3 mRNA expression via RT-qPCR. Immunohistochemistry was performed to evaluate the protein expression of DERL3 in LUAD tissues. The GEPIA and TIMER website were used to evaluate the correlation between DERL3 and immune cell infiltration. We further used the t-SNE map to visualize the distribution of DERL3 in various clusters at the single-cell level via TISCH database. The potential mechanisms of the biological process mediated by DERL3 in LUAD were conducted via KEGG and GSEA.

Results

It was indicated that DERL3 was predominantly elevated in carcinoma compared with adjacent tissues in multiple kinds of tumors from the TCGA database, especially in LUAD. Immunohistochemistry validated that DERL3 was also upregulated in LUAD tissues compared with adjacent tissues from individuals. DERL3 was preliminarily found to be associated with immune infiltration via the TIMER database. Further, the t-SNE map revealed that DERL3 was predominantly enriched in plasma cells of the B cell population. It was demonstrated that DERL3 high-expressed patients presented significantly worse response to chemotherapy and immunotherapy. GSEA and KEGG results indicated that DERL3 was positively correlated with B cell activation and unfolded protein response (UPR).

Conclusion

Our findings indicated that DERL3 might play an essential role in the endoplasmic reticulum-associated degradation (ERAD) process in LUAD. Moreover, DERL3 may act as a promising immune biomarker, which could predict the efficacy of immunotherapy in LUAD.

Intestinal Microbiota: The Driving Force behind Advances in Cancer Immunotherapy

Simple Summary

Despite the great achievements of cancer immunotherapy in a variety of tumors, tumor heterogeneity and drug resistance still plague patients and clinical researchers. In particular, the occurrence of immune-related adverse events forces patients to discontinue cancer immunotherapy. Therefore, it is urgent to optimize cancer immunotherapy and improve the efficacy of immunotherapy. With the iteration of sequencing technology, the microbiome, as the second set of genomes in the body, has been proven to be involved in immunity and metabolism. More and more studies are gradually shifting the perspective to the intestinal microbiota and cancer immunotherapy. The intestinal microbiota reactivates and modulates immune cells in immunotherapy and is expected to become a biomarker for predicting immune efficacy. Targeting to improve the intestinal microbiota can enhance anti-tumor immunity. This advantage is beneficial to control related adverse symptoms and expand the beneficiary population of cancer immunotherapy. This finding can help clinicians comprehensively evaluate the effect of tumor screening and tumor treatment. Therefore, the innovative combination of gut microbiota and cancer immunotherapy is expected to be an active strategy to enhance individualized immune responses.

Abstract

In recent years, cancer immunotherapy has become a breakthrough method to solve solid tumors. It uses immune checkpoint inhibitors to interfere with tumor immune escape to coordinate anti-tumor therapy. However, immunotherapy has an individualized response rate. Moreover, immune-related adverse events and drug resistance are still urgent issues that need to be resolved, which may be attributed to the immune imbalance caused by immune checkpoint inhibitors. Microbiome research has fully revealed the metabolic-immune interaction relationship between the microbiome and the host. Surprisingly, sequencing technology further proved that intestinal microbiota could effectively intervene in tumor immunotherapy and reduce the incidence of adverse events. Therefore, cancer immunotherapy under the intervention of intestinal microbiota has innovatively broadened the anti-tumor landscape and is expected to become an active strategy to enhance individualized responses.

CD8+ T cell trajectory subtypes decode tumor heterogeneity and provide treatment recommendations for hepatocellular carcinoma

Introduction

Mounting evidence has revealed that the interactions and dynamic alterations among immune cells are critical in shaping the tumor microenvironment and ultimately map onto heterogeneous clinical outcomes. Currently, the underlying clinical significance of immune cell evolutions remains largely unexplored in hepatocellular carcinoma (HCC).

Methods

A total of 3,817 immune cells and 1,750 HCC patients of 15 independent public datasets were retrieved. The Seurat and Monocle algorithms were used to depict T cell evolution, and nonnegative matrix factorization (NMF) was further applied to identify the molecular classification. Subsequently, the prognosis, biological characteristics, genomic variations, and immune landscape among distinct clusters were decoded. The clinical efficacy of multiple treatment approaches was further investigated.

Results

According to trajectory gene expression, three heterogeneous clusters with different clinical outcomes were identified. C2, with a more advanced pathological stage, presented the most dismal prognosis relative to C1 and C3. Eight independent external cohorts validated the robustness and reproducibility of the three clusters. Further explorations elucidated C1 to be characterized as lipid metabolic HCC, and C2 was referred to as cell-proliferative HCC, whereas C3 was defined as immune inflammatory HCC. Moreover, C2 also displayed the most conspicuous genomic instability, and C3 was deemed as “immune-hot”, having abundant immune cells and an elevated expression of immune checkpoints. The assessments of therapeutic intervention suggested that patients in C1 were suitable for transcatheter arterial chemoembolization treatment, and patients in C2 were sensitive to tyrosine kinase inhibitors, while patients in C3 were more responsive to immunotherapy. We also identified numerous underlying therapeutic agents, which might be conducive to clinical transformation in the future.

Conclusions

Our study developed three clusters with distinct characteristics based on immune cell evolutions. For specifically stratified patients, we proposed individualized treatment strategies to improve the clinical outcomes and facilitate the clinical management.

Genomic Landscape, Clinical Features and Outcomes of Non-Small Cell Lung Cancer Patients Harboring BRAF Alterations of Distinct Functional Classes

Simple Summary

Non-small cell lung cancer (NSCLC) patients harboring BRAF non-V600 alterations constitute a heterogeneous and poorly studied population orphan of targeted therapies. We conducted a systematic review to detect all BRAF alterations of defined functional class across different cancer types. Then, we searched for NSCLC patients harboring these alterations in the cancer bioportal and in POPLAR and OAK trials using patient-level data, to investigate clinical and genomic differences associated with each BRAF functional class and the prognostic impact of BRAF non-V600 mutations. We found that NSCLC patients harboring distinct classes of BRAF alterations have different clinical characteristics, clinical features and genomic landscape. Moreover, BRAF non-V600 alterations were associated with a poor prognostic impact, apparently regardless of the treatment received. These peculiar features may suggest the use of tailored treatments according to each class of BRAF alteration.

Abstract

Background: In non-small cell lung cancer (NSCLC), BRAF class 1 alterations are effectively targeted by BRAF inhibitors. Conversely, targeted therapies have very low or absent activity in patients carrying class 2 and 3 alterations. The spectrum of BRAF alterations in NSCLC patients, and their accompanying clinical features, genomic landscape and treatment outcomes have been poorly reported. Patients and methods: We identified BRAF alterations of defined functional class across different tumors through a systematic review. Then, we selected NSCLC patients carrying BRAF alterations, according to the systematic review, in the cBioPortal (cBioPortal cohort) to collect and analyze clinical, biomolecular and survival data. Finally, we identified NSCLC patients carrying BRAF non-V600 mutations enrolled in POPLAR and OAK trials (POPLAR/OAK cohort), extracting clinical and survival data for survival analyses. Results: 100 different BRAF non-V600 alterations were identified through the systematic review. In the cBioPortal cohort (n = 139), patients harboring class 2 and 3 alterations were more frequently smokers and had higher tumor mutational burden compared to those carrying class 1 alterations. The spectrum of most frequently co-altered genes was significantly different between BRAF alterations classes, including SETD2, STK11, POM121L12, MUC16, KEAP1, TERT, TP53 and other genes. In the POPLAR/OAK cohort, patients carrying non-V600 BRAF alterations were characterized by poor prognosis compared to BRAF wild-type patients. Conclusions: Different classes of BRAF alterations confer distinctive clinical features, biomolecular signature and disease behavior to NSCLC patients. Non-V600 alterations are characterized by poor prognosis, but key gene co-alterations involved in cancer cell survival and immune pathways may suggest their potential sensitivity to tailored treatments.

Hepatocellular Carcinoma Intrinsic Cell Death Regulates Immune Response and Prognosis

Ablative and locoregional treatment options, such as radiofrequency, ethanol injection, microwave, and cryoablation, as well as irreversible electroporation, are effective therapies for early-stage hepatocellular carcinoma (HCC). Hepatocyte death caused by ablative procedures is known to increase the release of tumor-associated antigen, thus enhancing tumor immunogenicity. In addition, the heat ablative resection induces pyroptotic cell death accompanied by the release of several inflammatory factors and immune-related proteins, including damage-associated molecular patterns (DAMPs), heat shock proteins (HSPs), ficolin 3, ATP, and DNA/RNA, which potentiate the antitumoral immune response. Surgical approaches that enhance tumor necrosis and reduce hypoxia in the residual liver parenchyma have been shown to increase the disease-free survival rate by reducing the host’s immunosuppressive response. Scalpel devices and targeted surgical approach combined with immune-modulating drugs are an interesting and promising area to maximize therapeutic outcomes after HCC ablation.

INK4 cyclin-dependent kinase inhibitors as potential prognostic biomarkers and therapeutic targets in hepatocellular carcinoma

The INK4 family is an important family of cyclin-dependent kinase inhibitors (CDKIs) and consists of CDKN2A, CDKN2B, CDKN2, and CDKN2D. Abnormal expression of CDKN2A has been reported in hepatocellular carcinoma (HCC) and is associated with the prognosis of patients and infiltration of immune cells. However, there is a lack of systematic research on the roles of the other INK4 family members in the diagnosis, prognosis, and immune regulation of HCC. Using online public databases and clinical samples, we comprehensively analyzed the INK4 family in HCC. All four INK4 proteins were overexpressed in HCC and correlated with advanced cancer stage and poor prognosis. INK4 expression accurately distinguished tumor from normal tissue, particularly CDKN2A and CDKN2C. The INK4 family participated in cell-cycle regulation and the DNA damage repair pathway, which inhibited genotoxic-induced apoptosis in tumorigenesis. INK4 proteins were positively correlated with the infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) and immune checkpoints (CTLA-4, PD1, and PD-L1). CDKN2D had the highest correlation (correlation coefficient >0.3) with all the above-mentioned infiltrating immune cells and immune checkpoints, indicating that it may be useful as an immunotherapy target. The INK4 family was valuable for diagnosis and predicting the prognosis of HCC and participated in the occurrence, progression, and immune regulation of HCC, demonstrating its potential as a diagnostic and prognostic biomarker and therapeutic target in HCC.

The Pyroptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immunotherapeutic Efficiency in Hepatocellular Carcinoma

Pyroptosis was recently demonstrated to be an inflammatory form of gasdermin-regulated programmed cell death characterized by cellular lysis and the release of several proinflammatory factors and participates in tumorigenesis. However, the effects of pyroptosis-related long noncoding RNAs (lncRNAs) on hepatocellular carcinoma (HCC) have not yet been completely elucidated. Based on the regression coefficients of ZFPM2-AS1, KDM4A-AS1, LUCAT1, NRAV, CRYZL2P-SEC16B, AL031985.3, SNHG4, AL049840.5, AC008549.1, MKLN1-AS, AC099850.3, and LINC01224, HCC patients were classified into a low- or high-risk group. The high-risk score according to pyroptosis-related lncRNA signature was significantly associated with poor overall survival even after adjusting for age and clinical stage. Receiver operating characteristic curves and principal component analysis further supported the accuracy of the model. Our study revealed that a higher pyroptosis-related lncRNA risk score was significantly associated with tumor staging, pathological grade, and tumor-node-metastasis stages. The nomogram incorporating the pyroptosis-related lncRNA risk score and clinicopathological factors demonstrated good accuracy. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. Notably, based on the risk model, we found that the risk score is closely related to the expression of immune checkpoint genes, immune subtypes of tumors, and the sensitivity of HCC to chemotherapy drugs and immunotherapy. In conclusion, our novel risk score of pyroptosis-related lncRNA can serve as a promising prognostic biomarker for HCC patients and provide help for HCC patients to guide precision drug treatment and immunotherapy.

Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort

Background

The incidence and mortality rates of colon adenocarcinoma (COAD), which is the fourth most diagnosed cancer worldwide, are high. A subset of patients with COAD has shown promising responses to immunotherapy. However, the percentage of patients with COAD benefiting from immunotherapy is unclear. Therefore, gaining a better understanding of the immune milieu of colon cancer could aid in the development of immunotherapy and suitable combination strategies.

Methods

In this study, gene expression profiles and clinical follow-up data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and molecular subtypes were identified using the ConsensusClusterPlus package in R. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic value of immune subtypes. The graph structure learning method was used to reduce the dimension to reveal the internal structure of the immune system. Weighted correlation network analysis (WGCNA) was performed to identify immune-related gene modules. Finally, western blotting was performed to verify the gene expression patterns in COAD samples.

Results

The results showed that 424 COAD samples could be divided into three subtypes based on 1921 immune cell-related genes, with significant differences in prognosis between subtypes. Furthermore, immune-related genes could be divided into five functional modules, each with a different distribution pattern of immune subtypes. Immune subtypes and gene modules were highly reproducible across many data sets. There were significant differences in the distribution of immune checkpoints, molecular markers, and immune characteristics among immune subtypes. Four core genes, namely, CD2, FGL2, LAT2, and SLAMF1, with prognostic significance were identified by WGCNA and univariate Cox analysis.

Conclusion

Overall, this study provides a conceptual framework for understanding the tumor immune microenvironment of colon cancer.

Construction of a Lactate-Related Prognostic Signature for Predicting Prognosis, Tumor Microenvironment, and Immune Response in Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent primary malignancies with high heterogeneity in the urological system. Growing evidence implies that lactate is a significant carbon source for cell metabolism and plays a vital role in tumor development, maintenance, and therapeutic response. However, the global influence of lactate-related genes (LRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response has not been comprehensively elucidated in patients with KIRC. In the present study, we collected RNA sequencing and clinical data of KIRC from The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts. Unsupervised clustering of 17 differentially expressed LRG profiles divided the samples into three clusters with distinct immune characteristics. Three genes (FBP1, HADH, and TYMP) were then identified to construct a lactate-related prognostic signature (LRPS) using the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. The novel signature exhibited excellent robustness and predictive ability for the overall survival of patients. In addition, the constructed nomogram based on the LRPS-based risk scores and clinical factors (age, gender, tumor grade, and stage) showed a robust predictive performance. Furthermore, patients classified by risk scores had distinguishable immune status, tumor mutation burden, response to immunotherapy, and sensitivity to drugs. In conclusion, we developed an LRPS for KIRC that was closely related to the immune landscape and therapeutic response. This LRPS may guide clinicians to make more precise and personalized treatment decisions for KIRC patients.

Comprehensive Analysis of HHLA2 as a Prognostic Biomarker and Its Association With Immune Infiltrates in Hepatocellular Carcinoma

Background

Inhibitory immune checkpoint proteins promote tumor immune escape and are associated with inferior patient outcome. However, the biological functions and regulatory roles of one of its members, HHLA2, in the tumor immune microenvironment have not been explored.

Methods

RandomForest analyses (371 cases), qRT-PCR (15 cases), and immunohistochemical staining (189 cases) were used to validate the prognostic value of HHLA2 in hepatocellular carcinoma (HCC) patients. Bioinformatic analyses were further performed to explore the biological functions and potential signaling pathways affected by HHLA2. Moreover, ESTIMATE, single sample gene set enrichment analysis, CIBERSORT, TIMER, and other deconvolution methods were used to analyze the composition and infiltration level of immune cells. Multiplex immunofluorescence assays were employed to validate the fractions of suppressive immune cells, and HHLA2-related molecular alterations were investigated. Finally, the clinical response to chemotherapy and immune checkpoint blockade was predicted by TIDE, Submap, and several other in silico analyses.

Results

RandomForest analysis revealed that HHLA2 was the most important inhibitory immune checkpoint associated with HCC patient prognosis (relative importance = 1). Our HCC cohorts further revealed that high HHLA2 expression was an independent prognostic biomarker of shorter overall survival (P<0.01) and time to recurrence (P<0.001) for HCC patients. Bioinformatics experiments revealed that HHLA2 may accelerate the cell cycle of cancer cells. Additionally, we found that high expression of HHLA2 was associated with immune infiltrates, including some immunosuppressive cells, cytokines, chemokines, and corresponding receptors, resulting in an immunosuppressive environment. Notably, HHLA2 expression was positively correlated with the infiltration of exhausted CD8+ T cells, which was validated by immunofluorescence. Genomic alteration analyses revealed that promoter hypermethylation of HHLA2 may be associated with its low expression. More importantly, patients with high HHLA2 expression may be more sensitive to chemotherapy and have better responses to immunotherapy.

Conclusions

High expression of HHLA2 is an independent prognostic biomarker for HCC patients. It can activate the cell cycle and foster an immunosuppressive tumor microenvironment by enriching exhausted CD8+ T cells. Promoter hypermethylation might lead to low expression of HHLA2 in HCC. Thus, targeting HHLA2 may be a practical therapeutic strategy for HCC patients in the future.

Multi-omics landscape and clinical significance of a SMAD4-driven immune signature: implications for risk stratification and frontline therapies in pancreatic cancer

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SMAD4 mutation affect the oncogenesis, progression and immunity of pancreatic cancer.

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Combined with immune subtypes, a SMAD4-driven immune signature (SDIS) was established.

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SDIS could robustly predict prognosis and efficacy in six independent cohorts.

•

SDIS might serve as an attractive platform to further tailor decision-making.

SMAD4 mutation was recently implicated in promoting invasion and poor prognosis of pancreatic cancer (PACA) by regulating the tumor immune microenvironment. However, SMAD4-driven immune landscape and clinical significance remain elusive. In this study, we applied the consensus clustering and weighted correlation network analysis (WGCNA) to identify two heterogeneous immune subtypes and immune genes. Combined with SMAD4-driven genes determined by SMAD4 mutation status, a SMAD4-driven immune signature (SDIS) was developed in ICGC-AU2 (microarray data) via machine learning algorithm, and then was validated by RNA-seq data (TCGA, ICGC-AU and ICGC-CA) and microarray data (GSE62452 and GSE85916). The high-risk group displayed a worse prognosis, and multivariate Cox regression indicated that SDIS was an independent prognostic factor. In six cohorts, SDIS also displayed excellent accuracy in predicting prognosis. Moreover, the high-risk group was characterized by higher frequencies of TP53/CDKN2A mutations and SMAD4 deletion, superior immune checkpoint molecules expression and more sensitive to chemotherapy and immunotherapy. Meanwhile, the low-risk group was significantly enriched in metabolism-related pathways and suggested the potential to target tumor metabolism to develop specific drugs. Overall, SDIS could robustly predict prognosis in PACA, which might serve as an attractive platform to further tailor decision-making in chemotherapy and immunotherapy in clinical settings.

Pan-Cancer Analysis Identified CD93 as a Valuable Biomarker for Predicting Patient Prognosis and Immunotherapy Response

Background: The rapid development of immunotherapy has significantly improved patient outcomes in recent years. CD93, a novel biomarker expressed on vascular endothelial cells, is essential for tumor angiogenesis. Recent studies have shown that CD93 is closely related to immune cell infiltration and immunotherapy. However, its role in pan-cancer has not been reported.

Methods: The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), cbioportal, Gene Expression Omnibus (GEO), Tumor Immune Estimation Resource (TIMER2.0), and the Tumor–Immune System Interactions and Drug Bank (TISIDB) databases were used to analyze CD93 in pan-cancers. R software was used for statistical analysis and mapping.

Results: There were significant differences in the expression of CD93 between tumor tissues and adjacent normal tissues in pan-cancer. The high expression of CD93 was associated with poor prognosis and high TNM stage in multiple tumor types. However, a high expression of CD93 was a protective factor in kidney renal clear cell carcinoma (KIRC). In addition, CD93 was closely related to immune cell infiltration in tumor tissues. Moreover, CD93 presented a robust correlation with immune modulators and immunotherapeutic markers [e.g., tumor mutation burden (TMB) and microsatellite instability (MSI)]. The results of gene set enrichment analysis (GSEA) showed that CD93 was correlated with tumor angiogenesis. Importantly, patients with a low expression of CD93 were more sensitive to immunotherapy in urothelial cancer.

Conclusion: CD93, which is involved in various immune responses, controls immune cell infiltration and impacts on the malignant properties of various cancer types. Therefore, CD93 has potential value to be biomarker for determining the prognosis and immune infiltration in multiple cancers.

Ferroptosis Mediation Patterns Reveal Novel Tool to Implicate Immunotherapy and Multi-Omics Characteristics in Bladder Cancer

Background: The regulatory role of ferroptosis in malignant tumours has been recently demonstrated. However, the potential roles of ferroptosis mediation patterns in bladder cancer remain elusive. Materials and Methods: The ferroptosis mediation patterns of 889 bladder cancer samples were comprehensively evaluated based on ferroptosis-related genes. The underlying correlations between these mediation patterns and multi-omic characteristics of bladder cancer were systematically analysed. The ferroptosis mediation patterns of individual samples were quantified by ferropscore using the principal component analysis algorithm. The typical ferroptosis-related genes with prognostic roles were further randomly validated using immunohistochemical staining, real-time polymerase chain reaction and western blotting. Results: Three different ferroptosis mediation patterns were identified. The abundance of infiltration of 23 immune cells was different among the three mediation patterns. The quantification of ferroptosis mediation patterns in individual samples served as a promising tool for predicting patient survival outcomes; immune cell infiltration abundance; tumour mutation burden; oncogenic mutation status and tumour grade, stage and molecular subtypes. Low ferropscore combined with high tumour mutation burden was associated with the best survival prognosis. Expressions of PD-L1 (p < 0.001), PD-1 (p = 0.002) and CTLA-4 (p = 0.003) were all significantly upregulated in the high ferropscore group. Low ferropscores also predicted good immunotherapy response for anti-CTLA4 strategy. The mRNA and protein levels of FADS2, a typical ferroptosis-related gene used in the study, were higher in bladder cancer cell lines than in controlled SV-HUC-1 cells. In addition, immunohistochemical staining revealed significantly higher expression levels of FADS2 in human bladder cancer tumour tissues than in normal tissues. Conclusion: This study identified three distinct ferroptosis mediation patterns in bladder cancer. Quantification of ferroptosis mediation patterns in individual samples may help to improve the understanding of multiomic characteristics and guide future immunotherapy responses to bladder cancer.

Interleukin-6 Is a Circulating Prognostic Biomarker for Hepatocellular Carcinoma Patients Treated with Combined Immunotherapy

Simple Summary

Hepatocellular carcinoma (HCC) is a major cause of cancer death worldwide. Due to its high recurrence rate, many HCC patients progress to an advanced stage and require systemic therapy. Among six available chemotherapy regimens for advanced HCC, atezolizumab/bevacizumab (Atezo/Bev) combination therapy is considered as a front-line therapy, but approximately 20% of patients are non-responders. Therefore, biomarker-driven prediction of non-responders facilitates precision medicine for HCC patients. To identify noninvasive circulating biomarkers predicting therapeutic response of Atezo/Bev, we performed simultaneous measurement of 34 plasma proteins and found that plasma IL-6 level was a significant predictor of non-responder for Atezo/Bev therapy. We subsequently confirmed that the progression-free survival and overall survival of the IL-6-high group were significantly shorter than those of the IL-6-low group. In conclusion, circulating IL-6 levels are a novel prognostic biomarker for advanced HCC patients who undergo combined immunotherapy.

Abstract

Atezolizumab/bevacizumab (Atezo/Bev) combination therapy has become a front-line therapy for advanced hepatocellular carcinoma (HCC), but approximately 20% of patients are nonresponders. We investigated circulating biomarkers to predict therapeutic outcomes. We performed simultaneous measurement of 34 proteins using a multiplex bead-based immunoassay in baseline plasma from 34 patients who underwent Atezo/Bev therapy as first- or second-line treatment. Logistic regression analysis showed that plasma IL-6 and interferon alpha (IFNα) levels were significant predictors of non-responders (odds ratio of 13.33 and FDR p = 0.021 for IL-6 and IFNα). The progression-free survival (PFS) and overall survival (OS) of patients with high IL-6 levels were significantly shorter than those of patients with low IL-6 levels. Next, we measured baseline plasma IL-6 levels in 64 HCC patients who underwent Atezo/Bev therapy by ELISA. The IL-6-high group showed higher female ratio, AST levels, tumor markers, Child–Pugh score, and vascular invasion ratio. The PFS and OS of the IL-6-high group were significantly shorter than those of the IL-6-low group. Multivariate Cox proportional hazards analysis showed that IL-6 level and age were independent risk factors for disease progression (hazard ratio of 2.785 and p = 0.015 for IL-6, and hazard ratio 0.306 and p = 0.03 for age). In conclusion, circulating IL-6 levels are a novel prognostic biomarker for advanced HCC patients who undergo combined immunotherapy.

Pt(II)-NHC Complex Induces ROS-ERS-Related DAMP Balance to Harness Immunogenic Cell Death in Hepatocellular Carcinoma

Immunogenic cell death (ICD) can engage a specific immune response and establish a long-term immunity in hepatocellular carcinoma (HCC). Herein, we design and synthesize a series of Pt(II)-N-heterocyclic carbene (Pt(II)-NHC) complexes derived from 4,5-diarylimidazole, which show strong anticancer activities in vitro. Among them, 2c displays much higher anticancer activities than cisplatin and other Pt(II)-NHC complexes, especially in HCC cancer cells. In addition, we find that 2c is a type II ICD inducer, which can successfully induce endoplasmic reticulum stress (ERS) accompanied by reactive oxygen species (ROS) generation and finally lead to the release of damage-associated molecular patterns (DAMPs) in HCC cells. Importantly, 2c shows a great anti-HCC potential in a vaccination mouse model and leads to the in vivo immune cell activation in the CCl4-induced liver injury model.

Histone Acetylation Regulator-Mediated Acetylation Patterns Define Tumor Malignant Pathways and Tumor Microenvironment in Hepatocellular Carcinoma

Background

Histone acetylation modification is one of the most common epigenetic methods used to regulate chromatin structure, DNA repair, and gene expression. Existing research has focused on the importance of histone acetylation in regulating tumorigenicity, tumor progression, and tumor microenvironment (TME) but has not explored the potential roles and interactions of histone acetylation regulators in TME cell infiltration, drug sensitivity, and immunotherapy.

Methods

The mRNA expression and genetic alterations of 36 histone acetylation regulators were analyzed in 1599 hepatocellular carcinoma (HCC) samples. The unsupervised clustering method was used to identify the histone acetylation patterns. Then, based on their differentially expressed genes (DEGs), an HAscore model was constructed to quantify the histone acetylation patterns and related subtypes of individual samples. Lastly, the relationship between HAscore and transcription background, tumor clinical features, characteristics of TME, drug response, and efficacy of immunotherapy were analyzed.

Results

We identified three histone acetylation patterns characterized by high, medium, and low HAscore. Patients with HCC in the high HAscore group experienced worse overall survival time, and the cancer-related malignant pathways were more active in the high HAscore group, comparing to the low HAscore group. The high HAscore group was characterized by an immunosuppressive subtype because of the high infiltration of immunosuppressive cells, such as regulatory T cells and myeloid-derived suppressor cells. Following validation, the HAscore was highly correlated with the sensitivity of anti-tumor drugs; 116 therapeutic agents were found to be associated with it. The HAscore was also correlated with the therapeutic efficacy of the PD-L1 and PD-1 blockade, and the response ratio was significantly higher in the low HAscore group.

Conclusion

To the best of our knowledge, our study is the first to provide a comprehensive analysis of 36 histone acetylation regulators in HCC. We found close correlations between histone acetylation patterns and tumor malignant pathways and TME. We also analyzed the therapeutic value of the HAscore in targeted therapy and immunotherapy. This work highlights the interactions and potential clinical utility of histone acetylation regulators in treatment of HCC and improving patient outcomes.

An Integrated Fibrosis Signature for Predicting Survival and Immunotherapy Efficacy of Patients With Hepatocellular Carcinoma

Introduction: Fibrosis, a primary cause of hepatocellular carcinoma (HCC), is intimately associated with inflammation, the tumor microenvironment (TME), and multiple carcinogenic pathways. Currently, due to widespread inter- and intra-tumoral heterogeneity of HCC, the efficacy of immunotherapy is limited. Seeking a stable and novel tool to predict prognosis and immunotherapy response is imperative. Methods: Using stepwise Cox regression, least absolute shrinkage and selection operator (LASSO), and random survival forest algorithms, the fibrosis-associated signature (FAIS) was developed and further validated. Subsequently, comprehensive exploration was conducted to identify distinct genomic alterations, clinical features, biological functions, and immune landscapes of HCC patients. Results: The FAIS was an independent prognostic predictor of overall survival and recurrence-free survival in HCC. In parallel, the FAIS exhibited stable and accurate performance at predicting prognosis based on the evaluation of Kaplan-Meier survival curves, receiver operator characteristic curves, decision curve analysis, and Harrell's C-index. Further investigation elucidated that the high-risk group presented an inferior prognosis with advanced clinical traits and a high mutation frequency of TP53, whereas the low-risk group was characterized by superior CD8⁺ T cell infiltration, a higher TIS score, and a lower TIDE score. Additionally, patients in the low-risk group might yield more benefits from immunotherapy. Conclusion: The FAIS was an excellent scoring system that could stratify HCC patients and might serve as a promising tool to guide surveillance, improve prognosis, and facilitate clinical management.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8⁺ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8⁺ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8⁺ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8⁺ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8⁺ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8⁺ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.

Identification of the Immune Cell Infiltration Landscape in Hepatocellular Carcinoma to Predict Prognosis and Guide Immunotherapy

Background: Globally, hepatocellular carcinoma (HCC) is the sixth most frequent malignancy with a high incidence and a poor prognosis. Immune cell infiltration (ICI) underlies both the carcinogenesis and immunogenicity of tumors. However, a comprehensive classification system based on the immune features for HCC remains unknown.

Methods: The HCC dataset from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts was used in this study. The ICI patterns of 571 patients were characterized using two algorithms: the patterns were determined based on the ICI using the ConsensusClusterPlus package, and principal component analysis (PCA) established the ICI scores. Differences in the immune landscape, biological function, and somatic mutations across ICI scores were evaluated and compared, followed by a predictive efficacy evaluation of ICI scores for immunotherapy by the two algorithms and validation using an external immunotherapy cohort.

Results: Based on the ICI profile of the HCC patients, three ICI patterns were identified, including three subtypes having different immunological features. Individual ICI scores were determined; the high ICI score subtype was characterized by enhanced activation of immune-related signaling pathways and a significantly high tumor mutation burden (TMB); concomitantly, diminished immunocompetence and enrichment of pathways associated with cell cycle and RNA degradation were found in the low ICI score subtype. Taken together, our results contribute to a better understanding of an active tumor and plausible reasons for its poor prognosis.

Conclusion: The present study reveals that ICI scores may serve as valid prognostic biomarkers for immunotherapy in HCC.

Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma

Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.

Materials and Methods: Hypoxia-related differentially expressed lncRNAs (HRDELs) were identified by conducting the differential gene expression analyses in GSE155505 and The Cancer Genome Atlas (TCGA)- liver hepatocellular carcinoma (LIHC) datasets. The HRDELs landscape in patients with HCC in TCGA-LIHC was dissected by an unsupervised clustering method. Patients in the TCGA-LIHC cohort were stochastically split into the training and testing dataset. The prognostic signature was developed using LASSO (least absolute shrinkage and selection operator) penalty Cox and multivariable Cox analyses. The tumor immune microenvironment was delineated by the single-sample gene set enrichment analysis (ssGSEA) algorithm. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to evaluate the predictive value of the constructed signature in immunotherapeutic responsiveness.

Results: A total of 55 HRDELs were identified through integrated bioinformatical analyses in GSE155505 and TCGA-LIHC. Patients in the TCGA-LIHC cohort were categorized into three HRDELs-specific clusters associated with different clinical outcomes. The prognostic signature involving five hypoxia-related lncRNAs (LINC00869, CAHM, RHPN1-AS1, MKLN1-AS, and DUXAP8) was constructed in the training dataset and then validated in the testing dataset and entire TCGA-LIHC cohort. The 5-years AUC of the constructed signature for prognostic prediction reaches 0.705 and is superior to that of age, AJCC stage, and histopathological grade. Patients with high-risk scores consistently had poorer overall survival outcomes than those with low-risk scores irrespective of other clinical parameters status. The low-risk group had more abundance in activated CD8⁺ T cell and activated B cell and were predicted to be more responsive to immunotherapy and targeted therapy than the high-risk group.

Conclusion: We established a reliable hypoxia-related lncRNAs signature that could accurately predict the clinical outcomes of HCC patients and correlate with immunotherapy response and targeted drug sensitivity, providing new insights for immunotherapy and targeted therapy in HCC.

A Prognostic Model of Pancreatic Cancer Based on Ferroptosis-Related Genes to Determine Its Immune Landscape and Underlying Mechanisms

Pancreatic cancer is one of the malignant tumors with the worst prognosis in the world. As a new way of programmed cell death, ferroptosis has been proven to have potential in tumor therapy. In this study, we used the TCGA-PAAD cohort combined with the previously reported 60 ferroptosis-related genes to construct and validate the prognosis model and in-depth analysis of the differences in the function and immune characteristics of different RiskTypes. The results showed that the six-gene signature prognostic model that we constructed has good stability and effectiveness. Further analysis showed that the upregulated genes in the high-risk group were mainly enriched in extracellular matrix receptor-related pathways and other tumor-related pathways and the infiltration of immune cells, such as B, T, and NK cells, was suppressed. In short, our model shows good stability and effectiveness. Further studies have found that the prognostic differences between different RiskTypes may be due to the changes in the ECM-receptor pathway and activation of the immune system. Additionally, ICI drugs can treat pancreatic cancer in high-risk groups.

Derivation and Clinical Validation of a Redox-Driven Prognostic Signature for Colorectal Cancer

Colorectal cancer (CRC), a seriously threat that endangers public health, has a striking tendency to relapse and metastasize. Redox-related signaling pathways have recently been extensively studied in cancers. However, the study and potential role of redox in CRC remain unelucidated. We developed and validated a risk model for prognosis and recurrence prediction in CRC patients via identifying gene signatures driven by redox-related signaling pathways. The redox-driven prognostic signature (RDPS) was demonstrated to be an independent risk factor for patient survival (including OS and RFS) in four public cohorts and one clinical in-house cohort. Additionally, there was an intimate association between the risk score and tumor immune infiltration, with higher risk score accompanied with less immune cell infiltration. In this study, we used redox-related factors as an entry point, which may provide a broader perspective for prognosis prediction in CRC and have the potential to provide more promising evidence for immunotherapy.

Tumor suppressor gene mutations correlate with prognosis and immunotherapy benefit in hepatocellular carcinoma

INTRODUCTION

The tumor microenvironment (TME) has profound impacts on prognosis and immunotherapy. The TME can be altered by the genomic mutations on specific tumor-suppressor genes (TSG), thus, comprehending the association between TME and TSG in hepatocellular carcinoma (HCC) is imperative.

METHODS

With a total of 1699 HCC patients from 6 international multicenter cohorts, we delineated the mutational landscape of TSG and summarized the proportion of TSG mutated HCC in different countries. Using the genomic and transcriptomic data, we comprehensively explored the impacts of TSG mutations on TME and immunity in HCC. A dataset of 31 HCC patients from the cBioPortal database was utilized to evaluate the predictive value of TSG subtypes for immunotherapy response.

RESULTS

Interestingly, TSG non-mutated HCC will have more "immune-hot" tumors, and display the infiltration abundance of immune cells such as B cell, CD4+/CD8+T cell, and neutrophil. Moreover, TSG non-mutated HCC was characterized by the higher expression level of three immune checkpoints, including CD40, CD40LG, and TNFRSF4. In line with the TME characterization and immune checkpoint profiles, TSG non-mutated HCC displayed prolonged overall survival and relapse-free survival, notably, are more likely to respond to immune checkpoint inhibitors.

CONCLUSIONS

Our findings suggested the TSG subtypes could serve as a promising biomarker for guiding surveillance protocol and immunotherapeutic decisions for patients with HCC.